I am rookie to using limma package. My data looks like this in excel: first column is the gene name, first raw is sample name, and under each sample name is the gene expression value (4 replicates per sample, I have sample wt and mu). I want to find out the significant expressed genes between mu vs wt.
and I write code like this:
sample=read.csv("sample.csv",header=T,row.names=1) logsample=log2(sample) design=model.matrix(~0+c(rep('wt',4),rep('mu',4))) colnames(design)=c("wt","mu") cm=makeContrasts(mu-wt,levels=design) fit=lmFit(logsample,design) fit2=contrasts.fit(fit,cm) fit3=eBayes(fit2) result=topTable(fit3,number=Inf,adjust="BH",sort.by="none")
I am not sure I did it correctly. Please help me to check, many thanks!! I log2 transformed the intensity. The data is already normalized by other software; I am not sure I should use makeContrasts or not.